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Researchers measured the percentage of fat in 240 samples of finely chopped pure meat (an expensive procedure in analytical chemistry) and also recorded the near-infrared absorbance spectrum at 100 equally spaced wavelengths in the range 850{1050 nanometres. The data are available as 101 columns of the file fatcontents.tab, the last column being the fat content.

The problem is to relate the fat content to the absorbance spectrum. It may be helpful to divide the fat content into ranges and only to predict if the meat is very low, low, medium, high or very high in fat, for example. You should bear in mind that the first 100 columns are the discretization of a continuous (if possibly spiky) curve for each meat sample, and that a more parsimonious summary of that curve will be needed (for example, only, via using a smoother on the data from each meat sample).

Your tasks are to

(a)    Present a clear visualization of the dataset.

(b)   Construct summaries for the absorbance spectra.

(c) Produce and validate a model to predict fat content.